An Adaptive WENO Collocation Method for Differential Equations with Random Coefficients

Wei Guo, Guang Lin, Andrew J. Christlieb and Jingmei Qiu
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Wei Guo: Department of Mathematics, Michigan State University, East Lansing, MI 48824; USA
Guang Lin: Department of Mathematics & School of Mechanical Engineering, Purdue University, West Lafayette, IN 47907, USA
Andrew J. Christlieb: Department of Mathematics, Michigan State University, East Lansing, MI 48824; USA
Jingmei Qiu: Department of Mathematics, University of Houston, Houston, TX 49931, USA

Mathematics, 2016, vol. 4, issue 2, 1-14

Abstract: The stochastic collocation method for solving differential equations with random inputs has gained lots of popularity in many applications, since such a scheme exhibits exponential convergence with smooth solutions in the random space. However, in some circumstance the solutions do not fulfill the smoothness requirement; thus a direct application of the method will cause poor performance and slow convergence rate due to the well known Gibbs phenomenon. To address the issue, we propose an adaptive high-order multi-element stochastic collocation scheme by incorporating a WENO (Weighted Essentially non-oscillatory) interpolation procedure and an adaptive mesh refinement (AMR) strategy. The proposed multi-element stochastic collocation scheme requires only repetitive runs of an existing deterministic solver at each interpolation point, similar to the Monte Carlo method. Furthermore, the scheme takes advantage of robustness and the high-order nature of the WENO interpolation procedure, and efficacy and efficiency of the AMR strategy. When the proposed scheme is applied to stochastic problems with non-smooth solutions, the Gibbs phenomenon is mitigated by the WENO methodology in the random space, and the errors around discontinuities in the stochastic space are significantly reduced by the AMR strategy. The numerical experiments for some benchmark stochastic problems, such as the Kraichnan-Orszag problem and Burgers’ equation with random initial conditions, demonstrate the reliability, efficiency and efficacy of the proposed scheme.

Keywords: stochastic collocation method; high-order; multi-element; WENO interpolation; adaptive mesh refinement (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2016
References: View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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